---
# id: openai
title: OpenAI
sidebar_label: OpenAI
---

By default, DeepEval uses `gpt-4o` to power all of its evaluation metrics. To enable this, you’ll need to set up your OpenAI API key. DeepEval also supports all other OpenAI models, which can be configured directly in Python.

### Setting Up Your API Key

To use OpenAI for `deepeval`'s LLM-Evals (metrics evaluated using an LLM), supply your `OPENAI_API_KEY` in the CLI:

```bash
export OPENAI_API_KEY=<your-openai-api-key>
```

Alternatively, if you're working in a notebook environment (Jupyter or Colab), set your `OPENAI_API_KEY` in a cell:

```bash
%env OPENAI_API_KEY=<your-openai-api-key>
```

### Python

You may use OpenAI models other than `gpt-4o`, which can be configured directly in python code through DeepEval's `GPTModel`.

:::info
You may want to use stronger reasoning models like `gpt-4o` for metrics that require a high level of reasoning — for example, a custom GEval for mathematical correctness.
:::

```python
from deepeval.models import GPTModel
from deepeval.metrics import AnswerRelevancyMetric

model = GPTModel(
    model="o1",
    temperature=0
)
answer_relevancy = AnswerRelevancyMetric(model=model)
```

There are **ONE** mandatory and **ONE** optional parameters when creating a `GPTModel`:

- `model`: A string specifying the name of the GPT model to use. Defaulted to `gpt-4o`.
- [Optional] `temperature`: A float specifying the model temperature. Defaulted to 0.

### Available OpenAI Models

:::note
This list only displays some of the available models. For a comprehensive list, refer to the OpenAI's official documentation.
:::

Below is a list of commonly used OpenAI models:

- `gpt-4.5-preview`
- `gpt-4o`
- `gpt-4o-mini`
- `o1`
- `o1-pro`
- `o1-mini`
- `o3-mini`
- `gpt-4-turbo`
- `gpt-4`
- `gpt-4-32k`
- `gpt-3.5-turbo`
- `gpt-3.5-turbo-instruct`
- `gpt-3.5-turbo-16k-0613`
- `davinci-002`
- `babbage-002`
